Microfluidics meets 3D cancer cell migration
Authors: Pranav Mehta, Zaid Rahman, Peter ten Dijke, Pouyan E. Boukany
Journal: Trends in cancer (2022)

Microfluidic cancer cell migration models enable an integrated assessment of how cell–cell and cell–matrix interaction, matrix stiffness, interstitial and shear flow, hypoxia and cytokine, and metabolic gradients affect dynamic cancer cell migration.While many in vitro static cell migration models fail to mimic the complexities and biomechanical features of the tumor microenvironment (TME), incorporation of microfluidics allows us to investigate cancer cell migration through the TME and invasion under well-controlled pathophysiological conditions associated with tumor progression events.Tumor cells can elicit distinct migratory behavior in the form of single or collective cell migration modes in response to extracellular biochemical and biophysical cues. An early step of metastasis requires a complex and coordinated migration of invasive tumor cells into the surrounding tumor microenvironment (TME), which contains extracellular matrix (ECM). It is being appreciated that 3D matrix-based microfluidic models have an advantage over conventional in vitro and animal models to study tumor progression events. Recent microfluidic models have enabled recapitulation of key mechanobiological features present within the TME to investigate collective cancer cell migration and invasion. Microfluidics also allows for functional interrogation and therapeutic manipulation of specific steps to study the dynamic aspects of tumor progression. In this review, we focus on recent developments in cancer cell migration and how microfluidic strategies have evolved to address the physiological complexities of the TME to visualize migration modes adapted by various tumor cells. An early step of metastasis requires a complex and coordinated migration of invasive tumor cells into the surrounding tumor microenvironment (TME), which contains extracellular matrix (ECM). It is being appreciated that 3D matrix-based microfluidic models have an advantage over conventional in vitro and animal models to study tumor progression events. Recent microfluidic models have enabled recapitulation of key mechanobiological features present within the TME to investigate collective cancer cell migration and invasion. Microfluidics also allows for functional interrogation and therapeutic manipulation of specific steps to study the dynamic aspects of tumor progression. In this review, we focus on recent developments in cancer cell migration and how microfluidic strategies have evolved to address the physiological complexities of the TME to visualize migration modes adapted by various tumor cells. Microfluidic modeling of cell invasionMetastasis, the spread of cancer cells away from the primary solid tumor and into the body's healthy tissues, eventually leading to the formation of secondary tumors causing organ failure, is responsible for over 90% of cancer-related deaths [1.Mitchell M.J. et al.Engineering and physical sciences in oncology: challenges and opportunities.Nat. Rev. Cancer. 2017; 17: 659-675Crossref PubMed Scopus (163) Google Scholar]. Metastasis requires the complex and coordinated migration of invasive tumor cells into the surrounding TME containing ECM. The TME plays a critical role in the early stages of metastasis, dictating cancer cell motility, invasion, and spread into neighboring tissues [2.Cox T.R. The matrix in cancer.Nat. Rev. Cancer. 2021; 21: 217-238Crossref PubMed Scopus (147) Google Scholar]. Key extracellular determinants of cancer cell migration include the biophysical and biochemical cues provided by the ECM, interstitial flow (IF), and cancer cell–TME interactions, including the interplay with cancer-associated fibroblasts (CAFs).Conventional tumor models previously used to study these cell motility mechanisms lie on either end of the spectrum: on one end, macroscopic in vitro models are easy and simple, but poorly recapitulate the local TME characteristics, including biomechanical forces, IF, fluid shear stress, and ECM remodeling. On the other end, animal models can mimic the pathophysiological complexity of tumors, but they are expensive, time-consuming, and still have a degree of error due to the innate differences between animal and human physiology. The use of microfluidics in 2D and 3D models has become an attractive alternative to overcome these challenges. Going a step further, microfluidics can more closely mimic the TME by incorporating various physiologically relevant biophysical and biological cues with precise spatiotemporal control (Figure 1, Key figure ) [3.Wan L. et al.Tumor-on-a-chip for integrating a 3D tumor microenvironment: chemical and mechanical factors.Lab Chip. 2020; 20: 873-888Crossref PubMed Google Scholar,4.Um E. et al.Cell migration in microengineered tumor environments.Lab Chip. 2017; 17: 4171-4185Crossref PubMed Google Scholar]. Microfluidic devices also permit real-time imaging of cellular dynamics, enabling them to probe biophysical, biochemical, and (epi)genetic activities present in healthy and diseased multicellular tissues [5.Huang Y.L. et al.Microfluidic modeling of the biophysical microenvironment in tumor cell invasion.Lab Chip. 2017; 17: 3221-3233Crossref PubMed Google Scholar]. The field of microfluidics continues to extend the development of tumor models ranging from tumor cancer spheroids to cancer-on-a-chip models with relevant TME and (patho)physiological conditions [6.Vunjak-Novakovic G. et al.Organs-on-a-chip models for biological research.Cell. 2021; 184: 4597-4611Abstract Full Text Full Text PDF PubMed Scopus (37) Google Scholar,7.Sontheimer-Phelps A. et al.Modelling cancer in microfluidic human organs-on-chips.Nat. Rev. Cancer. 2019; 19: 65-81Crossref PubMed Scopus (371) Google Scholar].Microfluidic platforms have been used for the study of the metastatic microenvironment, tumor–stroma interactions, and the TME in cancer metastasis and therapy [8.Tsai H.-F. et al.Tumour-on-a-chip: microfluidic models of tumour morphology, growth and microenvironment.J. R. Soc. 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However, a critical perspective on microfluidic approaches for mechanistic studies of cancer cell migration into surrounding TME, for example, how cancer cells adapt their migratory behavior through different TME, is still missing. Here, we discuss how cancer cells adapt their migration strategies through different and dynamically changing TMEs, and how novel microfluidics platforms have evolved to unravel the mechanisms of collective cancer cell migration through a tunable TME. We discuss how microfluidics is an effective tool to mimic the metastatic microenvironment for mechanistic investigations (Figure 1). We then discuss the underlying migration mechanisms adopted by cancer cells in a physiologically relevant TME model. We focus on lung and breast cancer cells as they are well studied but remain two of the most diagnosed cancers worldwide in terms of incidence and mortality due to the complexity of the TME [1.Mitchell M.J. et al.Engineering and physical sciences in oncology: challenges and opportunities.Nat. Rev. Cancer. 2017; 17: 659-675Crossref PubMed Scopus (163) Google Scholar,2.Cox T.R. The matrix in cancer.Nat. Rev. Cancer. 2021; 21: 217-238Crossref PubMed Scopus (147) Google Scholar]. Next, we highlight the role of tumor heterogeneity, ECM, interstitial and shear flow as biomechanical stimuli, CAFs, and the cytokine, transforming growth factor beta (TGF-β) as relevant biochemical cues to emphasize tumor invasion properties. Finally, we discuss challenges and new directions in applying 3D matrix-based microfluidic devices in personalized medicine and cancer therapy.Microfluidics in collective cell migrationBoth biophysical and cellular cues alter tumor cell responses (from migration modes to the level of invasiveness) inside the dynamic TME, resulting in the dissemination of cancer cells from the primary tumor. 3D in vitro tumor models such as heterogeneous or coculture multicellular spheroid models are widely used to investigate cancer cell migration and invasion [10.Xu H. et al.Recent advances in microfluidic models for cancer metastasis research.TrAC - Trends Anal. Chem. 2018; 105: 1-6Crossref Scopus (12) Google Scholar]. Static (no-flow) 3D cell culture models have been used to examine cell migration through semipermeable membranes or to study the biological response to specific chemoattractants or drugs [13.Ma Y.-H.V. et al.A review of microfluidic approaches for investigating cancer extravasation during metastasis.Microsyst. Nanoeng. 2018; 4: 1-13Crossref PubMed Google Scholar]. Moreover, a programmable and multifunctional 3D cancer cell invasion platform has been recently developed that dynamically releases mature TGF-β to induce invasive migration of cancer cells by assembling functionalized micro-buckets and a tunable ECM that emulates a more complex TME during cancer invasion [19.Liu Q. et al.A programmable multifunctional 3D cancer cell invasion micro platform.Small. 2022; (Published online March 9, 2022)https://doi.org/10.1002/smll.202107757Google Scholar]. A major advantage of using 3D microfluidic platforms is that different cell types can be cocultured long term in a controlled microenvironment, thus more closely resembling physiology in vivo. Through real-time visualization and the ability to study specific biological cues, 3D microfluidic platforms allow the characterization of individual cellular responses, providing insight into intercellular communication. For example, 3D matrix-based microfluidic models incorporated the use of endothelial cell (EC)-covered microchannels and spatiotemporally controlled ECM compartments consisting of stromal cells, tumor-associated macrophages (TAMs), CAFs, and immune cells to recreate intratumor heterogeneity [13.Ma Y.-H.V. et al.A review of microfluidic approaches for investigating cancer extravasation during metastasis.Microsyst. Nanoeng. 2018; 4: 1-13Crossref PubMed Google Scholar,20.Wang M. et al.Role of tumor microenvironment in tumorigenesis.J. 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Other 3D microfluidic models explored the use of patient-derived cells [9.Rodrigues J. et al.3D In vitro model (R)evolution: unveiling tumor–stroma interactions.Trends Cancer. 2021; 7: 249-264Abstract Full Text Full Text PDF PubMed Scopus (87) Google Scholar,22.Guo Q.R. et al.Multifunctional microfluidic chip for cancer diagnosis and treatment.Nanotheranostics. 2021; 5: 73-89Crossref PubMed Scopus (16) Google Scholar], response of natural killer (NK) or immune cells [23.Paterson K. et al.Microfluidic technologies for immunotherapy studies on solid tumours.Lab Chip. 2021; 21: 2306-2329Crossref PubMed Google Scholar], and drug delivery for drug screening applications [24.Valente K.P. et al.Microfluidic technologies for anticancer drug studies.Drug Discov. Today. 2017; 22: 1654-1670Crossref PubMed Scopus (53) Google Scholar,25.Shang M. et al.Microfluidic modelling of the tumor microenvironment for anti-cancer drug development.Lab Chip. 2019; 19: 369-386Crossref PubMed Google Scholar]. Researchers have also been able to reconstitute ex vivo a human tumor ecosystem by coculturing four distinct cell populations (cancer, immune, endothelial, and fibroblasts) in a microfluidic device in 3D. Using this platform to screen for drug interactions and mechanisms, researchers elucidated cancer–immune–CAF cell interactions, illustrating the long-time scale (several hours) signaling cascade between cancer and immune cells and CAFs that antagonized the effects of the drug.3D microfluidic models create a more effective and powerful platform to track intermediate steps to differentiate between single and collective cell migration mechanisms in cancer models with a dynamic interplay of multiple (dynamically phenotypically changing) cell types [26.Paul C.D. et al.Engineered models of confined cell migration.Annu. Rev. Biomed. Eng. 2016; 18: 159-180Crossref PubMed Scopus (69) Google Scholar] (Box 1). Various microfluidic models have been developed to investigate metastasis-related phenomena, such as cancer cell migration, epithelial-mesenchymal transition (EMT), cell invasion, intravasation, and extravasation. In the following sections, we take a closer look at the microfluidic models developed for lung and breast cancers highlighting microfluidic modeling parameters and improved biological outcomes. Furthermore, these (3D) microfluidic devices have been adapted to investigate the impact of TME complexity on a wide variety of tumor invasions. An overview of 3D microfluidic models for various cancer types modeled for different tumor progression events and with chemotherapeutic applications is provided in Table 1.Box 1Migration dynamics and epithelial-mesenchymal plasticity (EMP)Cell migration can be broadly classified into two modes, individual or single-cell migration and collective cell migration. Morphologically and functionally, single-cell migration can be further classified into amoeboidal and mesenchymal movement. Amoeboid single migrating cells often display structures referred to as plasma membrane blebs, defined by a bulky and rounded morphology, and these blebs are an extension of the plasma membrane caused by local disruption of the membrane actin cortex interactions, high intracellular hydrostatic pressure, and enhanced contractility [66.Parri M. Chiarugi P. Rac and Rho GTPases in cancer cell motility control.Cell Commun. Signal. 2010; 8: 1-14Crossref PubMed Scopus (440) Google Scholar,67.Te Boekhorst V. et al.Plasticity of cell migration in vivo and in silico.Annu. Rev. Cell Dev. Biol. 2016; 32: 491-526Crossref PubMed Scopus (130) Google Scholar]. Single cells displaying a mesenchymal migration mode, moreover, display actin-rich protrusions and rely on the proteolytic degradation of the surrounding ECM [68.Wolf K. et al.Compensation mechanism in tumor cell migration: mesenchymal-amoeboid transition after blocking of pericellular proteolysis.J. Cell Biol. 2003; 160: 267-277Crossref PubMed Scopus (1139) Google Scholar,69.Balzer E.M. et al.Physical confinement alters tumor cell adhesion and migration phenotypes.FASEB J. 2012; 26: 4045-4056Crossref PubMed Scopus (178) Google Scholar].Collective migration occurs when cells maintain their intercellular junctions and thus migrate jointly as an integrated group. The collective morphology and dynamics of cohesive motility are strongly dependent on the type and stability of their intercellular junctions and extracellular tissue conditions [67.Te Boekhorst V. et al.Plasticity of cell migration in vivo and in silico.Annu. Rev. Cell Dev. Biol. 2016; 32: 491-526Crossref PubMed Scopus (130) Google Scholar]. Collective migration in cancer is characterized by the expression of homophilic cell–cell junctions and epithelial morphologies within the migrating cluster [70.Friedl P. Mayor R. Tuning collective cell migration by cell-cell junction regulation.Cold Spring Harb. Perspect. Biol. 2017; 9: 1-18Crossref Scopus (170) Google Scholar]. Protrusive cells at the leading edge, termed leader cells, are connected to the rest of the cluster and have been shown to coordinate multicellular sheet/strand migration [71.Qin L. et al.Roles of leader and follower cells in collective cell migration.Mol. Biol. Cell. 2021; 32: 1267-1272Crossref PubMed Scopus (8) Google Scholar]. Collectively migrating cancer cells display structural ECM remodeling, further promoting migration and metastasis [72.Anguiano M. et al.The use of mixed collagen-Matrigel matrices of increasing complexity recapitulates the biphasic role of cell adhesion in cancer cell migration: ECM sensing, remodeling and forces at the leading edge of cancer invasion.PLoS One. 2020; 15e0220019Crossref PubMed Scopus (41) Google Scholar]. Cellular plasticity, the ability to repress or activate specific gene expression and modulate the activity of gene products to allow for optimal migration mechanics or survival, is crucial for collective cell migration. This plasticity allows migrating cancer cells to integrate various mechanical and chemical cues around them and adjust their direction, speed, and mode of migration [67.Te Boekhorst V. et al.Plasticity of cell migration in vivo and in silico.Annu. Rev. Cell Dev. Biol. 2016; 32: 491-526Crossref PubMed Scopus (130) Google Scholar].Epithelial cancer cells can undergo a switch to a mesenchymal phenotype, a process termed epithelial–to–mesenchymal transition (EMT) [73.Yang J. Weinberg R.A. Epithelial-mesenchymal transition: at the crossroads of development and tumor metastasis.Dev. Cell. 2008; 14: 818-829Abstract Full Text Full Text PDF PubMed Scopus (2417) Google Scholar]. New studies show that EMT is a dynamic plastic process, where cells can acquire different hybrid intermediate states called partial EM states (p-EMT), a process referred to EMP [74.Aiello N.M. et al.EMT subtype influences epithelial plasticity and mode of cell migration.Dev. Cell. 2018; 45: 681-695.e4Abstract Full Text Full Text PDF PubMed Scopus (304) Google Scholar,75.Yang J. et al.Guidelines and definitions for research on epithelial–mesenchymal transition.Nat. Rev. Mol. Cell Biol. 2020; 21: 341-352Crossref PubMed Scopus (586) Google Scholar]. In such states, cells retain various epithelial features while also expressing EMT markers such as N-cadherin and vimentin intermediate filaments [67.Te Boekhorst V. et al.Plasticity of cell migration in vivo and in silico.Annu. Rev. Cell Dev. Biol. 2016; 32: 491-526Crossref PubMed Scopus (130) Google Scholar]. Cells undergoing complete EMT (c-EMT) transcriptionally suppress the epithelial markers such as the transmembrane protein E-cadherin [74.Aiello N.M. et al.EMT subtype influences epithelial plasticity and mode of cell migration.Dev. Cell. 2018; 45: 681-695.e4Abstract Full Text Full Text PDF PubMed Scopus (304) Google Scholar].Table 13D microfluidic models to study cancer cell migration and anticancer therapeutic approaches in different tumor typesCancer typeMicrofluidic model highlightsBiological observations/outcomeLimitationsRefsBreast cancerType: tumor invasionCells: SUM-159 breast cancer cells and CAF coculture3D microfluidic based organotypic model. Focuses on tumor invasion by stromal activation. Coculture of SUM-159 and patient-derived fibroblasts to model patient-specific TME. Allows for tumor–stroma crosstalk.RNA-seq is applied to profile the transcriptome of breast cancer cells with CAFs to delve deeper into molecular mechanisms in tumor–stroma bidirectional crosstalk.Breast cancer invasion enhanced in the presence of CAFs, is mediated by the expression of glycoprotein nonmetastatic B (GPNMB) in breast cancer cells.Patient-derived CAFs heterogeneously express varying levels of specific biomarkers. Two out of three patient-derived CAFs showed tumor-promoting behavior.No defined single or set of biomarkers was defined owing to CAF heterogeneity.[83.Truong D.D. et al.A human organotypic microfluidic tumor model permits investigation of the interplay between patient-derived fibroblasts and breast cancer cells.Cancer Res. 2019; 79: 3139-3151Crossref PubMed Scopus (66) Google Scholar]Type: hypoxia-driven tumor migrationCells: HUVECs, MCF-10A, MDA-MB-231, MCF-7 and normal human lung fibroblasts (NHLFs)Microfluidic model consisting of vascular networks to quantify breast cancer extravasation when exposed to different oxygen concentrations.Device with three-gel channels, alternated with media channels. An advantage in the study of different cell lines and conditions of normoxia and varying hypoxia levels in short-term cultures.Increase in hypoxia inducible factor (HIF)-1α protein levels in hypoxic conditions were linked to elevated levels of metastatic potential. The increase in aggressive phenotype under hypoxic conditions is independent of the malignancy of different cell lines.Effect of hypoxia on cell proliferation and viability can be different in cells lines of varying malignancy based on short-term or long-term exposure to hypoxic conditions.More studies are needed to understand the signaling pathways responsible for hypoxia-induced increased metastatic potential.[84.Song J. et al.A 3D microvascular network model to study the impact of hypoxia on the extravasation potential of breast cell lines.Sci. Rep. 2018; 8: 1-11Crossref PubMed Scopus (34) Google Scholar]Type: tumor extravasationCells: MDA-MB-231 breast cancer cells, monocytesA 3D vascularized microfluidic model that provides high-resolution visualization of intravascular migration, transmigration, and differentiation of monocytes through human vasculature.Characterization of tumor cell extravasation in the presence of monocytes.Physiological differences between inflammatory and patrolling monocyte extravasation patterns were measured by the platform.Potential to study effects of monocytes on tumor progression.Undifferentiated monocytes present with MDA-MB-231 cancer cells in intraluminal vasculature reduced tumor cell extravasation.Heterogeneity of cancer cell in extravasation mediated by monocyte type was observed. This difference was attributed to the role of myosin IIA in monocyte cell motility.Future studies should examine media conditioned by cells in 3D compared with 2D system conditioned medium.More studies need to be performed on monocyte homeostasis and extravasation cascade in response to flow.Incorporation of other immune cells.[85.Boussommier-Calleja A. et al.The effects of monocytes on tumor cell extravasation in a 3D vascularized microfluidic model.Biomaterials. 2019; 198: 180-193Crossref PubMed Scopus (69) Google Scholar]Lung cancerType: tumor migrationCells: H1299 lung adenocarcinoma cancer cellsA 3D matrix-based microfluidic device with mixed hydrogel (collagen, Matrigel) compositions to investigate impact on migration.Quantitative image analysis to measure H1299 lung cancer migration in different hydrogel (ECM) compositions.Hydrogel composition mimicking the TME. A disorganized basement membrane at the front of cancer invasion was mimicked using an ECM containing hydrogel.An increase in migration speed in collagen-Matrigel hydrogel compared with collagen only was observed because of increased stiffness and pore size.Hydrogel composition was identified as an important determinant for cell migration.Inconsistency with results on migration speed and morphology with increasing matrix stiffness and pore sizes.Difficult to identify the exact composition of in vivo ECM based on specific cancer types and their location.[86.Anguiano M. et al.Characterization of three-dimensional cancer cell migration in mixed collagen-Matrigel scaffolds using microfluidics and image analysis.PLoS One. 2017; 12e0171417Crossref PubMed Scopus (82) Google Scholar]Type: tumor migration and anticancer therapy responseCells: A549 lung cancer cells, miR-497 exosomes.A 3D microfluidic device in which A549 lung cancer cells and HUVECs are cocultured that is capable of delivery and controlled regulation of miRNAs via exosomes to explore therapeutic potential.The model permitted the study of the role of VEGF concentration gradient on angiogenic sprouting.miRNA therapeutics combined with microfluidics for a predictive, low-cost development tool for targeted cancer therapy.Significant inhibition of A549 cell migration and reduced sprouting of HUVECs was observed in the presence of miR-497 exosomes.Exosomes containing miR-497 suppressed tumor growth and expression of associated genes.The model does not consider the inclusion of additional cell types such as CAFs and/or immune cells and hypoxic gradients.The role of ECM composition in the lung TME and the mechanical strain on the lung remains uncharacterized.[87.Jeong K. et al.Exosome-mediated microRNA-497 delivery for anti-cancer therapy in a microfluidic 3D lung cancer model.Lab Chip. 2020; 20: 548-557Crossref PubMed Google Scholar]Pancreatic ductal adenocarcinoma (PDAC)Type: heterogeneous tumor invasionCells: pancreatic cell (PCC) lineA complex and heterogeneous PDAC model was developed by embedding a duct of genetically engineered PCCs surrounded by collagen matrix.Precisely controlled intratumoral heterogeneity was engineered to enable heterogeneous invasion characteristics as a response to TGF-β1 on EMT and local invasion.Confirmation of TGF-β1 promoting EMT and local invasion in different PCC lines.Study revealed complex interaction between different cancer cells making them more aggressive and invasive. Model can be used to study interaction between heterogeneous patient-derived cancer and stromal cells.The microfluidic model falls short to incorporate CAFs and other ECM components as a part of pancreatic TME.[88.Bradney M.J. et al.A biomimetic tumor model of heterogeneous invasion in pancreatic ductal adenocarcinoma.Small. 2020; 16: 1-10Crossref Scopus (17) Google Scholar]Type: tumor progressionCells: PANC-1 pancreatic cells and pancreatic stellate cellsMicrofluidic models using pancreatic stellate cells (PSCs) to study their role in cancer progression and drug resistance.Coculture of pancreatic tumor spheroids (made of PANC-1 cells) with PSCs in 3D collagen matrix to mimic in vivo TME to visualize EMT and quantify chemoresistance.Expression of EMT markers such as vimentin, TIMP1, interleukin (IL)-8, and TGF-β was higher in cocultured PANC-1 spheroids compared with monocultures. PANC-1 cells also showed greater cell motility.EMT leads to drug resistance, mediated by the TME components such as stromal cells and their interactions with cancer cells.Contradicting results when using different CAFs targeting strategies raises an issue of intratumoral CAF heterogeneity.[89.Lee J.H. et al.Microfluidic co-culture of pancreatic tumor spheroids with stellate cells as a novel 3D model for investigation of stroma-mediated cell motility and drug resistance.J. Exp. Clin. Cancer Res. 2018; 37: 1-12Crossref PubMed Scopus (92) Google Scholar]Prostate cancerType: chemotherapeutic responseCells: DU 145 prostate cancer cellsMicrofluidic platform representing a 3D TME for rapid evaluation of chemotherapeutic drugs on different cancer cells.Multiple chambers equipped with perfusion channels allows screening of multiple drugs to determine the right combination in a patient-specific manner.Integration of electrical sensing modality with microfluidics to measure electrical (impedance) response of a cancer cell upon exposure through dynamic drug delivery in a 3D matrix environment.The proposed platform enabled the differentiation between drug susceptible, drug tolerant/resistant cancer cells in less than 12 hours.Impedance measurement of cells seeded in gel provided information on cell growth, morphology, and cell density.Potential to study patient-derived samples for personalized medicine in a rapid, low-cost approach for real-time drug screening analysis.Polydimethylsiloxane (PDMS)-based microfluidic devices have the disadvantage of being porous to molecules less than 500 Da. These molecules can be absorbed creating a difference in the concentration of drugs.[90.Pandya H.J. et al.A microfluidic platform for drug screening in a 3D cancer microenvironment.Biosens. Bioelectron. 2017; 94: 632-642Crossref PubMed Scopus (46) Google Scholar]MelanomaType: tumor migrationCells: fibroblast and keratinocyteEquipped with air walls to pattern cells without using conventional hydrogel barriers. Consists of circular chambers with narrow connections.Ability to coculture melanoma cells with keratinocytes and dermal fibroblasts. Air walls dissolve progressively and allows cellular crosstalk and